Enhancing Health through Social Determinants of Health Screening in Primary Care and Community Partnerships
Bibliographic record
Abstract
Background: Screening for social determinants of health (SDOH) is not routine in primary care. The Calgary Foothills Primary Care Network (PCN) implemented SDOH screening in clinics to identify needs and partnered with Distress Centre/2 to navigate and connect patients to community resources, enhancing patient support and access to services. Approach: The one-year pilot project was grant-funded by the City of Calgary Addiction and Mental Health Strategy and involved a partnership between the PCN, Distress Centre Calgary 2 Alberta Service (herein referred to as 2), and Alberta Health Services (AHS). Key stakeholders from the PCN, providers, physician clinics, and 2 designed, implemented and monitored a closed-loop referral process to improve the identification of patients in need and the access and continuity of care between medical clinics and community services.Adult patients at participating PCN physician clinics were offered an SDOH screening questionnaire that assessed for financial, social, or safety needs. Patients who identified at least one need were offered a referral to 2 or a PCN social worker. The 2 service outreached to referred patients to complete a needs assessment and provide a list of available community resources. The 2 service completed a follow-up phone call and survey with the patient to assess if the resource(s) had met their needs. Finally, 2 closed the loopby sending a final disposition to the family physician. Results: Twenty-four member physicians at four clinics participated in the initiative. ,7 patients completed the screening questionnaire (84%), with 228 patients (n=20%) who screened positive for social and financial needs. This demonstrated the screening was an acceptable and appropriate setting to identify patients with SDOH needs. The questionnaire results showed that most needs were related to financial difficulty. Of the people who screened positive (n=228), 7% had difficulty making ends meet, 48% had trouble affording medications, 35% felt unsupported by friends or family, 4% had difficulty accessing food, and 2% felt unsafe where they were living. There were challenges connecting patients with resources, as only 56 patients who screened positive consented and were referred to 2. The 2 services successfully connected with 3 patients (23%) and provided patients with linkages to a total of 45 resources. 84% of patients indicated they felt comfortable answering the screening questions in the medical clinic. Implications: This initiative found that screening for SDOH in the medical home can effectively and appropriately identify people who may have financial, social or safety concerns. Furthermore, physicians and staff agreed and found value in screening for SDOH in primary care. However, there were gaps in connecting patients with identified needs to the 2-navigation service and linked to supportive community resources. This warrants further exploration with patients to understand their preferences, wants and needs for support and improve future interventions' design. By working collaboratively on this project, primary care providers, member clinics, and external partners learned more about the respective groups' services, roles and improved communication and integration of services. Future opportunities include simplified screening workflows, education and awareness about SDOH, organizational health equity measures and continued integration activities with patients and partners.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".